Hello,
I am trying to perform Regression with target distribution assumed to be Weibull.
The input is a time-ordered sequence with each timestamp having a regression target.
At each timestamp, the input is a mix of categorical and numerical values.
I transformed categorical variables using embedding and numerical values using an FFN.
When I train the network using LSTM, I am getting constant values as output, irrespective of the input.
Not sure how to debug/inspect this problem.
I am new to Pytorch, so I am confused.
Any suggestions wil be helpful.